Today you can use MySQL in several clouds in what is considered using it as a service, a database as a service (DBaaS). Learn the differences, the access methods, and the level of control you have for the various cloud offerings including:
- Amazon RDS
- Google Cloud SQL
- HPCloud DBaaS
- Rackspace Openstack DBaaS
The administration tools and ideologies behind it are completely different, and you are in a "locked-down" environment. Some considerations include:
* Different backup strategies
* Planning for multiple data centres for availability
* Where do you host your application?
* How do you get the most performance out of the solution?
* What does this all cost?
Questions like this will be demystified in the talk.
(GAM301) Real-Time Game Analytics with Amazon Kinesis, Amazon Redshift, and A...Amazon Web Services
Success in free-to-play gaming requires knowing what your players love most. The faster you can respond to players' behavior, the better your chances of success. Learn how mobile game company GREE, with over 150 million users worldwide, built a real-time analytics pipeline for their games using Amazon Kinesis, Amazon Redshift, and Amazon DynamoDB. They walk through their analytics architecture, the choices they made, the challenges they overcame, and the benefits they gained. Also hear how GREE migrated to the new system while keeping their games running and collecting metrics.
#lspe Q1 2013 dynamically scaling netflix in the cloudCoburn Watson
Meetup presentation on how Netflix dynamically scales in the cloud. It covers topics primarily related to AWS autoscaling and provides some "day-in-the-life" data.
Real-time Streaming and Querying with Amazon Kinesis and Amazon Elastic MapRe...Amazon Web Services
Originally, Hadoop was used as a batch analytics tool; however, this is rapidly changing, as applications move towards real-time processing and streaming. Amazon Elastic MapReduce has made running Hadoop in the cloud easier and more accessible than ever. Each day, tens of thousands of Hadoop clusters are run on the Amazon Elastic MapReduce infrastructure by users of every size — from university students to Fortune 50 companies. We recently launched Amazon Kinesis – a managed service for real-time processing of high volume, streaming data. Amazon Kinesis enables a new class of big data applications which can continuously analyze data at any volume and throughput, in real-time. Adi will discuss each service, dive into how customers are adopting the services for different use cases, and share emerging best practices. Learn how you can architect Amazon Kinesis and Amazon Elastic MapReduce together to create a highly scalable real-time analytics solution which can ingest and process terabytes of data per hour from hundreds of thousands of different concurrent sources. Forever change how you process web site click-streams, marketing and financial transactions, social media feeds, logs and metering data, and location-tracking events.
If you want to break your monolith into components, services, or even functions, it is important to understand where and how to break your existing code base and architecture into smaller units to allow it to scale and perform, and to make it easy to operate. This session, a representative from Dynatrace shows how the company redefined its architecture, explains which migration capabilities its engineers built into its product, and describes how the lessons learned can benefit everyone as they fearlessly transform from monolith to serverless.
Build Your Web Analytics with node.js, Amazon DynamoDB and Amazon EMR (BDT203...Amazon Web Services
Want to learn how to build your own Google Analytics? Learn how to build a scalable architecture using node.js, Amazon DynamoDB, and Amazon EMR. This architecture is used by ScribbleLive to track billions of engagement minutes per month. In this session, we go over the code in node.js, how to store the data in Amazon DynamoDB, and how to roll-up the data using Hadoop and Hive. Attend this session to learn how to move data quickly at any scale as well as how to use genomic analysis tools and pipelines for next generation sequencers using Globus on AWS.
Scaling your Application for Growth using Automation (CPN209) | AWS re:Invent...Amazon Web Services
Growing too quickly may sound like a nice problem to have, unless you are the one having it. A growing business can’t afford not to keep up with customer demand and availability. Don’t be left behind. Come learn how start-ups Chute and Euclid kept up with real-time user-generated data from over 3,000 apps and 2 TB of metadata and stayed ahead of retail peak-time traffic, all with AWS. Hear how they used all that data on their own growth to propel their business even further and deepen relationships with customers. Not planning for growth is just like not planning to grow!
Comparing Cloud VM Types and Prices: AWS vs Azure vs Google vs IBMRightScale
In today’s multi-cloud world, you need to understand how VM types and prices compare between public clouds. Whether you are comparing clouds to find the best placement, benchmarking your compute costs, or want to migrate between clouds, you’ll find out how to map the instance types and how costs will vary by cloud provider.
(GAM301) Real-Time Game Analytics with Amazon Kinesis, Amazon Redshift, and A...Amazon Web Services
Success in free-to-play gaming requires knowing what your players love most. The faster you can respond to players' behavior, the better your chances of success. Learn how mobile game company GREE, with over 150 million users worldwide, built a real-time analytics pipeline for their games using Amazon Kinesis, Amazon Redshift, and Amazon DynamoDB. They walk through their analytics architecture, the choices they made, the challenges they overcame, and the benefits they gained. Also hear how GREE migrated to the new system while keeping their games running and collecting metrics.
#lspe Q1 2013 dynamically scaling netflix in the cloudCoburn Watson
Meetup presentation on how Netflix dynamically scales in the cloud. It covers topics primarily related to AWS autoscaling and provides some "day-in-the-life" data.
Real-time Streaming and Querying with Amazon Kinesis and Amazon Elastic MapRe...Amazon Web Services
Originally, Hadoop was used as a batch analytics tool; however, this is rapidly changing, as applications move towards real-time processing and streaming. Amazon Elastic MapReduce has made running Hadoop in the cloud easier and more accessible than ever. Each day, tens of thousands of Hadoop clusters are run on the Amazon Elastic MapReduce infrastructure by users of every size — from university students to Fortune 50 companies. We recently launched Amazon Kinesis – a managed service for real-time processing of high volume, streaming data. Amazon Kinesis enables a new class of big data applications which can continuously analyze data at any volume and throughput, in real-time. Adi will discuss each service, dive into how customers are adopting the services for different use cases, and share emerging best practices. Learn how you can architect Amazon Kinesis and Amazon Elastic MapReduce together to create a highly scalable real-time analytics solution which can ingest and process terabytes of data per hour from hundreds of thousands of different concurrent sources. Forever change how you process web site click-streams, marketing and financial transactions, social media feeds, logs and metering data, and location-tracking events.
If you want to break your monolith into components, services, or even functions, it is important to understand where and how to break your existing code base and architecture into smaller units to allow it to scale and perform, and to make it easy to operate. This session, a representative from Dynatrace shows how the company redefined its architecture, explains which migration capabilities its engineers built into its product, and describes how the lessons learned can benefit everyone as they fearlessly transform from monolith to serverless.
Build Your Web Analytics with node.js, Amazon DynamoDB and Amazon EMR (BDT203...Amazon Web Services
Want to learn how to build your own Google Analytics? Learn how to build a scalable architecture using node.js, Amazon DynamoDB, and Amazon EMR. This architecture is used by ScribbleLive to track billions of engagement minutes per month. In this session, we go over the code in node.js, how to store the data in Amazon DynamoDB, and how to roll-up the data using Hadoop and Hive. Attend this session to learn how to move data quickly at any scale as well as how to use genomic analysis tools and pipelines for next generation sequencers using Globus on AWS.
Scaling your Application for Growth using Automation (CPN209) | AWS re:Invent...Amazon Web Services
Growing too quickly may sound like a nice problem to have, unless you are the one having it. A growing business can’t afford not to keep up with customer demand and availability. Don’t be left behind. Come learn how start-ups Chute and Euclid kept up with real-time user-generated data from over 3,000 apps and 2 TB of metadata and stayed ahead of retail peak-time traffic, all with AWS. Hear how they used all that data on their own growth to propel their business even further and deepen relationships with customers. Not planning for growth is just like not planning to grow!
Comparing Cloud VM Types and Prices: AWS vs Azure vs Google vs IBMRightScale
In today’s multi-cloud world, you need to understand how VM types and prices compare between public clouds. Whether you are comparing clouds to find the best placement, benchmarking your compute costs, or want to migrate between clouds, you’ll find out how to map the instance types and how costs will vary by cloud provider.
Real-time Streaming and Querying with Amazon Kinesis and Amazon Elastic MapRe...Amazon Web Services
Originally, Hadoop was used as a batch analytics tool; however, this is rapidly changing, as applications move towards real-time processing and streaming. Amazon Elastic MapReduce has made running Hadoop in the cloud easier and more accessible than ever. Each day, tens of thousands of Hadoop clusters are run on the Amazon Elastic MapReduce infrastructure by users of every size — from university students to Fortune 50 companies. We recently launched Amazon Kinesis – a managed service for real-time processing of high volume, streaming data. Amazon Kinesis enables a new class of big data applications which can continuously analyze data at any volume and throughput, in real-time. Adi will discuss each service, dive into how customers are adopting the services for different use cases, and share emerging best practices. Learn how you can architect Amazon Kinesis and Amazon Elastic MapReduce together to create a highly scalable real-time analytics solution which can ingest and process terabytes of data per hour from hundreds of thousands of different concurrent sources. Forever change how you process web site click-streams, marketing and financial transactions, social media feeds, logs and metering data, and location-tracking events.
In this session, Kevin will dive into the unique challenges of keeping your Kubernetes workloads highly available while keeping costs low. You will learn about how to leverage cloud-native autoscaling, pod requirement right-sizing, resource buffer definition, cost allocation and more.
Surge 2013: Maximizing Scalability, Resiliency, and Engineering Velocity in t...Coburn Watson
Surge 2013 presentation which covers how Netflix maximizes engineering velocity while keeping risks to scalability, reliability, and performance in check.
Cloud Price Comparison - AWS vs Azure vs GoogleRightScale
Cloud pricing is complicated. It can be difficult to compare cloud prices because providers offer different pricing models, unique discounting options, frequent price cuts, and promises to match prices. We sort through the noise and provide a reality check on which providers have the lowest-cost compute and storage options and in which circumstances.
Aws Summit Berlin 2013 - Understanding database options on AWSAWS Germany
With AWS you can choose the right database for the right job. Given the myriad of choices, from relational databases to non-relational stores, this session will profile details and examples of some of the choices available to you (MySQL, RDS, Elasticache, Redis, Cassandra, MongoDB and DynamoDB), with details on real world deployments from customers using Amazon RDS, ElastiCache and DynamoDB.
NASA LandSat data can be stored, transformed, navigated, and visualized. In this session we will explore how the LandSat dataset is stored in Amazon Simple Storage Service (S3), one of the recommended cloud storage services in AWS for storage of petabytes of data, and how data stored in S3 can be processed on the server with the Lambda service, visualized for users, and made available to search engines.
Create by: Ben Snively, Senior Solutions Architect
Getting to 1.5M Ads/sec: How DataXu manages Big DataQubole
DataXu sits at the heart of the all-digital world, providing a data platform that manages tens of millions of dollars of digital advertising investments from Global 500 brands. The DataXu data platform evaluates 1.5 million online ad opportunities every second for our customers, allowing them to manage and optimize their marketing investments across all digital channels. DataXu employs a wide range of AWS services: Cloud Front, Cloud Trail, CloudWatch, Data Pipeline, Direct Connect, Dynamo DB, EC2, EMR, Glacier, IAM, Kinesis, RDS, Redshift, Route53, S3, SNS, SQS, and VPC to run various workloads at scale for DataXu data platform.
In addition, DataXu also uses Qubole Data Service, QDS, to offer a Unified Analytics Interface tool to DataXu customers. Qubole, a member of APN provides self-managing Big data infrastructure in the Cloud which leverages spot pricing for cost-efficiencies, provides fast performance, and most importantly a streamlined user-interface for ease of use.
Attendees will learn how Qubole provided self-managing Hadoop clusters in the AWS Cloud accelerated DataXu’s batch-oriented analysis jobs; and how Qubole integration with Amazon Redshift enabled DataXu to preform low latency and interactive analysis. Further, in the session we'll take a look at how DataXu opened up QDS access to their customers using QDS user interface thereby providing them with a single tool for both batch-oriented and interactive analysis. By using the QDS user interface buyers of the DataXu data service could perform all manner of analysis against the data stored in their AWS S3 bucket.
Speakers:
Scott Ward
Solutions Architect at Amazon Web Services
Ashish Dubey
Solutions Architect at Qubole
Yekesa Kosuru
VP Engineering at DataXu
(BDT201) Big Data and HPC State of the Union | AWS re:Invent 2014Amazon Web Services
Leveraging big data and high performance computing (HPC) solutions enables your organization to make smarter and faster decisions that influence strategy, increase productivity, and ultimately grow your business. We kick off the Big Data and HPC track with the latest advancements in data analytics, databases, storage, and HPC at AWS. Hear customer success stories and discover how to put data to work in your own organization.
Cloud storage costs are increasing and now represent a significant portion of cloud spend. As a result, cloud users need to focus on ways to reduce storage spend by selecting the best options while also finding ways to manage the rapid increase in the use of cloud storage.
Join us for a for a Amazon Kinesis tutorial webinar. In this session we will provide a reference architecture and instructions for building a system that performs real-time sliding-windows analysis over streaming clickstream data. We will use Amazon Kinesis for managed ingestion of streaming data at scale with the ability to replay past data, and run sliding-window computation using Apache Storm. We’ll demonstrate in the webinar on how to build the system and deploy on AWS and walkthrough all the steps from ingestion, processing, and storing to visualizing of the data in real-time.
Visit http:aws.amazon.com/hpc for more information about HPC on AWS.
High Performance Computing (HPC) allows scientists and engineers to solve complex science, engineering, and business problems using applications that require high bandwidth, low latency networking, and very high compute capabilities. AWS allows you to increase the speed of research by running high performance computing in the cloud and to reduce costs by providing Cluster Compute or Cluster GPU servers on-demand without large capital investments. You have access to a full-bisection, high bandwidth network for tightly-coupled, IO-intensive workloads, which enables you to scale out across thousands of cores for throughput-oriented applications.
Hive + Amazon EMR + S3 = Elastic big data SQL analytics processing in the cloudJaipaul Agonus
This presentation is a real-world case study about moving a large portfolio of batch analytical programs that process 30 billion or more transactions every day, from a proprietary MPP database appliance architecture to the Hadoop ecosystem in the cloud, leveraging Hive, Amazon EMR, and S3.
goto; London: Keeping your Cloud Footprint in CheckCoburn Watson
Presented on the "Lean" track at goto; London September 17th, 2015. Covers how Netflix manages cloud cost efficiency in light of innovation and reliability drivers.
Managing Your Cloud Spend With PlanForCloud - RightScale Compute 2013RightScale
Speaker: Hassan Khajeh-Hosseini - PlanForCloud Product Lead, RightScale
Learn the ins and outs of cloud cost management, including forecasting, comparisons, scenario modeling, and cost reporting. We will demonstrate how to use PlanForCloud and RightScale reporting to improve the cost information you have about your cloud applications.
Google’s Committed Use Discounts vs. AWS Reserved Instances and More Ways to ...RightScale
Google Cloud Platform has lower pricing for infrastructure-as-a-service versus other cloud providers for many use cases. In addition, Google recently announced Committed Use Discounts, which provide a competitive offering to AWS Reserved Instances. Find out how Google Cloud Platform pricing compares and how to get the most savings for a variety of use cases.
Cloud Storage Comparison: AWS vs Azure vs Google vs IBMRightScale
As public cloud storage services mature, it becomes easier to make apples-to-apples comparisons. We drill down on the latest specs and features for object, block, archival, and file storage across AWS, Azure, Google, and IBM. We also compare prices for a variety of storage scenarios.
Workload-Aware: Auto-Scaling A new paradigm for Big Data WorkloadsVasu S
Learn more about Workload-Aware-Auto-Scaling-- an alternative architectural approach to Auto-Scaling that is better suited for the Cloud and applications like Hadoop, Spark, and Presto.
qubole.com/resources/white-papers/workload-aware-auto-scaling-qubole
Next Generation Cloud Computing With Google - RightScale Compute 2013RightScale
Speaker: Martin Gannholm - Lead Engineer, Google
Google Cloud Platform provides everything you need to build, run, and scale social, mobile, and online applications. Already, tens of thousands of popular applications like Khan Academy, Angry Birds, SnapChat, and Pulse are benefiting from the power of running on top of Google infrastructure. Come join Google as we go deep on how to best leverage our technology with RightScale to build your next masterpiece.
Today you can use hosted MySQL/MariaDB/Percona Server in several "cloud providers" in what is considered using it as a service, a database as a service (DBaaS). You can also use hosted PostgreSQL and MongoDB thru various service providers. Learn the differences, the access methods, and the level of control you have for the various public cloud offerings:
- Amazon RDS for MySQL and PostgreSQL
- Google Cloud SQL
- Rackspace OpenStack DBaaS
- The likes of compose.io, MongoLab and Rackspace's offerings around MongoDB
The administration tools and ideologies behind it are completely different, and you are in a "locked-down" environment. Some considerations include:
* Different backup strategies
* Planning for multiple data centres for availability
* Where do you host your application?
* How do you get the most performance out of the solution?
* What does this all cost?
Growth topics include:
* How do you move from one DBaaS to another?
* How do you move all this from DBaaS to your own hosted platform?
Questions like this will be demystified in the talk. This talk will benefit experienced database administrators (DBAs) who now also have to deal with cloud deployments as well as application developers in startups that have to rely on "managed services" without the ability of a DBA.
Do you wonder how to contribute to MariaDB? Have you considered writing a plugin? MariaDB ships many plugins (over a hundred) and you could also be one of them. Find out what they do, how to use them, and so forth. A lightning talk given for the MySQL NL User Group meetup in Amsterdam.
Real-time Streaming and Querying with Amazon Kinesis and Amazon Elastic MapRe...Amazon Web Services
Originally, Hadoop was used as a batch analytics tool; however, this is rapidly changing, as applications move towards real-time processing and streaming. Amazon Elastic MapReduce has made running Hadoop in the cloud easier and more accessible than ever. Each day, tens of thousands of Hadoop clusters are run on the Amazon Elastic MapReduce infrastructure by users of every size — from university students to Fortune 50 companies. We recently launched Amazon Kinesis – a managed service for real-time processing of high volume, streaming data. Amazon Kinesis enables a new class of big data applications which can continuously analyze data at any volume and throughput, in real-time. Adi will discuss each service, dive into how customers are adopting the services for different use cases, and share emerging best practices. Learn how you can architect Amazon Kinesis and Amazon Elastic MapReduce together to create a highly scalable real-time analytics solution which can ingest and process terabytes of data per hour from hundreds of thousands of different concurrent sources. Forever change how you process web site click-streams, marketing and financial transactions, social media feeds, logs and metering data, and location-tracking events.
In this session, Kevin will dive into the unique challenges of keeping your Kubernetes workloads highly available while keeping costs low. You will learn about how to leverage cloud-native autoscaling, pod requirement right-sizing, resource buffer definition, cost allocation and more.
Surge 2013: Maximizing Scalability, Resiliency, and Engineering Velocity in t...Coburn Watson
Surge 2013 presentation which covers how Netflix maximizes engineering velocity while keeping risks to scalability, reliability, and performance in check.
Cloud Price Comparison - AWS vs Azure vs GoogleRightScale
Cloud pricing is complicated. It can be difficult to compare cloud prices because providers offer different pricing models, unique discounting options, frequent price cuts, and promises to match prices. We sort through the noise and provide a reality check on which providers have the lowest-cost compute and storage options and in which circumstances.
Aws Summit Berlin 2013 - Understanding database options on AWSAWS Germany
With AWS you can choose the right database for the right job. Given the myriad of choices, from relational databases to non-relational stores, this session will profile details and examples of some of the choices available to you (MySQL, RDS, Elasticache, Redis, Cassandra, MongoDB and DynamoDB), with details on real world deployments from customers using Amazon RDS, ElastiCache and DynamoDB.
NASA LandSat data can be stored, transformed, navigated, and visualized. In this session we will explore how the LandSat dataset is stored in Amazon Simple Storage Service (S3), one of the recommended cloud storage services in AWS for storage of petabytes of data, and how data stored in S3 can be processed on the server with the Lambda service, visualized for users, and made available to search engines.
Create by: Ben Snively, Senior Solutions Architect
Getting to 1.5M Ads/sec: How DataXu manages Big DataQubole
DataXu sits at the heart of the all-digital world, providing a data platform that manages tens of millions of dollars of digital advertising investments from Global 500 brands. The DataXu data platform evaluates 1.5 million online ad opportunities every second for our customers, allowing them to manage and optimize their marketing investments across all digital channels. DataXu employs a wide range of AWS services: Cloud Front, Cloud Trail, CloudWatch, Data Pipeline, Direct Connect, Dynamo DB, EC2, EMR, Glacier, IAM, Kinesis, RDS, Redshift, Route53, S3, SNS, SQS, and VPC to run various workloads at scale for DataXu data platform.
In addition, DataXu also uses Qubole Data Service, QDS, to offer a Unified Analytics Interface tool to DataXu customers. Qubole, a member of APN provides self-managing Big data infrastructure in the Cloud which leverages spot pricing for cost-efficiencies, provides fast performance, and most importantly a streamlined user-interface for ease of use.
Attendees will learn how Qubole provided self-managing Hadoop clusters in the AWS Cloud accelerated DataXu’s batch-oriented analysis jobs; and how Qubole integration with Amazon Redshift enabled DataXu to preform low latency and interactive analysis. Further, in the session we'll take a look at how DataXu opened up QDS access to their customers using QDS user interface thereby providing them with a single tool for both batch-oriented and interactive analysis. By using the QDS user interface buyers of the DataXu data service could perform all manner of analysis against the data stored in their AWS S3 bucket.
Speakers:
Scott Ward
Solutions Architect at Amazon Web Services
Ashish Dubey
Solutions Architect at Qubole
Yekesa Kosuru
VP Engineering at DataXu
(BDT201) Big Data and HPC State of the Union | AWS re:Invent 2014Amazon Web Services
Leveraging big data and high performance computing (HPC) solutions enables your organization to make smarter and faster decisions that influence strategy, increase productivity, and ultimately grow your business. We kick off the Big Data and HPC track with the latest advancements in data analytics, databases, storage, and HPC at AWS. Hear customer success stories and discover how to put data to work in your own organization.
Cloud storage costs are increasing and now represent a significant portion of cloud spend. As a result, cloud users need to focus on ways to reduce storage spend by selecting the best options while also finding ways to manage the rapid increase in the use of cloud storage.
Join us for a for a Amazon Kinesis tutorial webinar. In this session we will provide a reference architecture and instructions for building a system that performs real-time sliding-windows analysis over streaming clickstream data. We will use Amazon Kinesis for managed ingestion of streaming data at scale with the ability to replay past data, and run sliding-window computation using Apache Storm. We’ll demonstrate in the webinar on how to build the system and deploy on AWS and walkthrough all the steps from ingestion, processing, and storing to visualizing of the data in real-time.
Visit http:aws.amazon.com/hpc for more information about HPC on AWS.
High Performance Computing (HPC) allows scientists and engineers to solve complex science, engineering, and business problems using applications that require high bandwidth, low latency networking, and very high compute capabilities. AWS allows you to increase the speed of research by running high performance computing in the cloud and to reduce costs by providing Cluster Compute or Cluster GPU servers on-demand without large capital investments. You have access to a full-bisection, high bandwidth network for tightly-coupled, IO-intensive workloads, which enables you to scale out across thousands of cores for throughput-oriented applications.
Hive + Amazon EMR + S3 = Elastic big data SQL analytics processing in the cloudJaipaul Agonus
This presentation is a real-world case study about moving a large portfolio of batch analytical programs that process 30 billion or more transactions every day, from a proprietary MPP database appliance architecture to the Hadoop ecosystem in the cloud, leveraging Hive, Amazon EMR, and S3.
goto; London: Keeping your Cloud Footprint in CheckCoburn Watson
Presented on the "Lean" track at goto; London September 17th, 2015. Covers how Netflix manages cloud cost efficiency in light of innovation and reliability drivers.
Managing Your Cloud Spend With PlanForCloud - RightScale Compute 2013RightScale
Speaker: Hassan Khajeh-Hosseini - PlanForCloud Product Lead, RightScale
Learn the ins and outs of cloud cost management, including forecasting, comparisons, scenario modeling, and cost reporting. We will demonstrate how to use PlanForCloud and RightScale reporting to improve the cost information you have about your cloud applications.
Google’s Committed Use Discounts vs. AWS Reserved Instances and More Ways to ...RightScale
Google Cloud Platform has lower pricing for infrastructure-as-a-service versus other cloud providers for many use cases. In addition, Google recently announced Committed Use Discounts, which provide a competitive offering to AWS Reserved Instances. Find out how Google Cloud Platform pricing compares and how to get the most savings for a variety of use cases.
Cloud Storage Comparison: AWS vs Azure vs Google vs IBMRightScale
As public cloud storage services mature, it becomes easier to make apples-to-apples comparisons. We drill down on the latest specs and features for object, block, archival, and file storage across AWS, Azure, Google, and IBM. We also compare prices for a variety of storage scenarios.
Workload-Aware: Auto-Scaling A new paradigm for Big Data WorkloadsVasu S
Learn more about Workload-Aware-Auto-Scaling-- an alternative architectural approach to Auto-Scaling that is better suited for the Cloud and applications like Hadoop, Spark, and Presto.
qubole.com/resources/white-papers/workload-aware-auto-scaling-qubole
Next Generation Cloud Computing With Google - RightScale Compute 2013RightScale
Speaker: Martin Gannholm - Lead Engineer, Google
Google Cloud Platform provides everything you need to build, run, and scale social, mobile, and online applications. Already, tens of thousands of popular applications like Khan Academy, Angry Birds, SnapChat, and Pulse are benefiting from the power of running on top of Google infrastructure. Come join Google as we go deep on how to best leverage our technology with RightScale to build your next masterpiece.
Today you can use hosted MySQL/MariaDB/Percona Server in several "cloud providers" in what is considered using it as a service, a database as a service (DBaaS). You can also use hosted PostgreSQL and MongoDB thru various service providers. Learn the differences, the access methods, and the level of control you have for the various public cloud offerings:
- Amazon RDS for MySQL and PostgreSQL
- Google Cloud SQL
- Rackspace OpenStack DBaaS
- The likes of compose.io, MongoLab and Rackspace's offerings around MongoDB
The administration tools and ideologies behind it are completely different, and you are in a "locked-down" environment. Some considerations include:
* Different backup strategies
* Planning for multiple data centres for availability
* Where do you host your application?
* How do you get the most performance out of the solution?
* What does this all cost?
Growth topics include:
* How do you move from one DBaaS to another?
* How do you move all this from DBaaS to your own hosted platform?
Questions like this will be demystified in the talk. This talk will benefit experienced database administrators (DBAs) who now also have to deal with cloud deployments as well as application developers in startups that have to rely on "managed services" without the ability of a DBA.
Do you wonder how to contribute to MariaDB? Have you considered writing a plugin? MariaDB ships many plugins (over a hundred) and you could also be one of them. Find out what they do, how to use them, and so forth. A lightning talk given for the MySQL NL User Group meetup in Amsterdam.
An introduction to MongoDB from an experienced MySQL user and developer. There are differences and we go thru the What/Why/Who/Where of MongoDB, the "similarities" to the MySQL world like storage engines, how replication is a little more interesting with built-in sharding and automatic failover, backups, monitoring, DBaaS, going to production and finding out more resources.
This is my third iteration of the talk presented in Tokyo, Japan - first was at a keynote at rootconf.in in April 2016, then at the MySQL meetup in New York, and now for dbtechshowcase. The focus is on database failures of the past, and how modern MySQL / MariaDB Server technologies could have helped them avoid such failure. The focus is on backups and verification, replication and failover, and security and encryption.
Failure happens, and we can learn from it. We need to think about backups, but also verification of them. We should definitely make use of replication and think about automatic failover. And security is key, but don't forget that encryption is now available in MySQL, Percona Server and MariaDB Server.
Presented at the MySQL Chicago Meetup in August 2016. The focus of the talk is on backups and verification, replication and failover, as well as security and encryption.
Securing your MySQL / MariaDB Server dataColin Charles
Co-presented alongside Ronald Bradford, this covers MySQL, Percona Server, and MariaDB Server (since the latter occasionally can be different enough). Go thru insecure practices, focus on communication security, connection security, data security, user accounts and server access security.
MariaDB 10.1 what's new and what's coming in 10.2 - Tokyo MariaDB MeetupColin Charles
Presented at the Tokyo MariaDB Server meetup in July 2016, this is an overview of what you can see and use in MariaDB Server 10.1, but more importantly what is planned to arrive in 10.2
Presented at Percona Live Amsterdam 2016, this is an in-depth look at MariaDB Server right up to MariaDB Server 10.1. Learn the differences. See what's already in MySQL. And so on.
MariaDB Server Compatibility with MySQLColin Charles
At the MariaDB Server Developer's meeting in Amsterdam, Oct 8 2016. This was the deck to talk about what MariaDB Server 10.1/10.2 might be missing from MySQL versions up to 5.7. The focus is on compatibility of MariaDB Server with MySQL.
Better encryption & security with MariaDB 10.1 & MySQL 5.7Colin Charles
Talking about the improvements in MariaDB on MySQL security and encryption features that are so important in today's data landscape. Presented http://www.meetup.com/EffectiveMySQL/events/224828891/
The Proxy Wars - MySQL Router, ProxySQL, MariaDB MaxScaleColin Charles
As proxies (and database routers) go, the first one I ever used was the now deprecated MySQL Proxy. Since then, I've managed to use MariaDB MaxScale quite a bit (including its fork AirBnB MaxScale), played around with ProxySQL in recent time, and also started taking a look at MySQL Router. In this quick 20-minute overview, we'll discuss why these three exist, a feature comparison, and reasons when to use the right tool for the job.
This was a short 25 minute talk, but we go into a bit of a history of MySQL, how the branches and forks appeared, what's sticking around today (branch? Percona Server. Fork? MariaDB Server). What should you use? Think about what you need today and what the roadmap holds.
Best practices for MySQL/MariaDB Server/Percona Server High AvailabilityColin Charles
Best practices for MySQL/MariaDB Server/Percona Server High Availability - presented at Percona Live Amsterdam 2016. The focus is on picking the right High Availability solution, discussing replication, handling failure (yes, you can achieve a quick automatic failover), proxies (there are plenty), HA in the cloud/geographical redundancy, sharding solutions, how newer versions of MySQL help you, and what to watch for next.
Forking Successfully - or is a branch better?Colin Charles
Forking Successfully or do you think a branch will work better? Learn from history, see what's current, etc. Presented at OSCON London 2016. This is forking beyond the github generation. And if you're going to do it, some tips on how you could be successful.
You want to use MySQL in Amazon RDS, Rackspace Cloud, Google Cloud SQL or HP Helion Public Cloud? Check this out, from Percona Live London 2014. (Note that pricing of Google Cloud SQL changed prices on the same day after the presentation)
MySQL in the Hosted Cloud - Percona Live 2015Colin Charles
You're a smaller shop and you want to host MySQL in the cloud, maybe because you don't have a database administrator on hand. Find out how to do it in Amazon's AWS EC2 or RDS, Google's Cloud SQL or even Rackspace's platform.
Presented at OSCON 2018. A review of what is available from MySQL, MariaDB Server, MongoDB, PostgreSQL, and more. Covering your choices, considerations, versions, access methods, cost, a deeper look at RDS and if you should run your own instances or not.
With a focus on Amazon AWS RDS MySQL and PostgreSQL, Rackspace cloud, Google Cloud SQL, Microsoft Azure for MySQL and PostgreSQL as well as a hint of the other clouds
Meet MariaDB 10.1 at the Bulgaria Web SummitColin Charles
Meet MariaDB 10.1 at the Bulgaria Web Summit, held in Sofia in February 2016. Learn all about MariaDB Server, and the new features like encryption, audit plugins, and more.
MariaDB - the "new" MySQL is 5 years old and everywhere (LinuxCon Europe 2015)Colin Charles
MariaDB is like the "new" MySQL, and its available everywhere. This talk was given at LinuxCon Europe in Dublin in October 2015. Learn about all the new features, considering the release was just around the corner. Changes in replication are also very interesting
MariaDB - a MySQL Replacement #SELF2014Colin Charles
MariaDB - a MySQL replacement at South East Linux Fest 2014 - SELF2014. Learn about features that are not in MySQL 5.6, some that are only just coming in MySQL 5.7, and some that just don't exist.
Scylla Summit 2022: How ScyllaDB Powers This Next Tech CycleScyllaDB
Applications have never been so data-hungry, nor as demanding for scale, speed and availability. Hear from CEO Dor Laor as he shares how ScyllaDB is powering this next tech cycle.
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
Webinar Slides: MySQL HA/DR/Geo-Scale - High Noon #4: MS Azure Database MySQLContinuent
MS Azure Database for MySQL vs. Continuent Tungsten Clusters
Building a Geo-Scale, Multi-Region and Highly Available MySQL Cloud Back-End
This is the third of our High Noon series covering MySQL clustering solutions for high availability (HA), disaster recovery (DR), and geographic distribution.
Azure Database for MySQL is a managed database cluster within Microsoft Azure Cloud that runs MySQL community edition. There are really two deployment options: “Single Server” and “Flexible Server (Preview).” We will look at the Flexible Server version, even though it is still preview, because most enterprise applications require failover, so this is the relevant comparison for Tungsten Clustering.
You may use Tungsten Clustering with native MySQL, MariaDB or Percona Server for MySQL in GCP, AWS, Azure, and/or on-premises data centers for better technological capabilities, control, and flexibility. But learn about the pros and cons!
Enjoy the webinar!
AGENDA
- Goals for the High Noon Webinar Series
- High Noon Series: Tungsten Clustering vs Others
- Microsoft Azure Database for MySQL
- Key Characteristics
- Certification-based Replication
- Azure MySQL Multi-Site Requirements
- Limitations Using Azure MySQL
- How to do better MySQL HA / DR / Geo-Scale?
- Azure MySQL vs Tungsten Clustering
- About Continuent & Its Solutions
PRESENTER
Matthew Lang - Customer Success Director – Americas, Continuent - has over 25 years of experience in database administration, database programming, and system architecture, including the creation of a database replication product that is still in use today. He has designed highly available, scaleable systems that have allowed startups to quickly become enterprise organizations, utilizing a variety of technologies including open source projects, virtualization and cloud.
Webinar Slides: MySQL HA/DR/Geo-Scale - High Noon #5: Oracle’s InnoDB ClusterContinuent
Oracle’s InnoDB Cluster vs. Continuent Tungsten Clusters for MySQL
Building a Geo-Distributed, Multi-Region and Highly Available MySQL Cloud Back-End
This is the fifth of our High Noon series covering MySQL clustering solutions for high availability (HA), disaster recovery (DR), and geographic distribution.
InnoDB Cluster uses MySQL’s group replication to handle the replication. It’s also known as semi-synchronous replication. Learn about this and more in this webinar!
You may use Tungsten Clustering with native MySQL, MariaDB or Percona Server for MySQL in GCP, AWS, Azure, and/or on-premises data centers for better technological capabilities, control, and flexibility. But learn about the pros and cons!
AGENDA
- Goals for the High Noon Webinar Series
- High Noon Series: Tungsten Clustering vs Others
- Oracle InnoDB Cluster
- Key Characteristics
- Certification-based Replication
- InnoDB Cluster Multi-Site Requirements
- Limitations Using InnoDB Cluster
- How to do better MySQL HA / DR / Geo-Distribution?
- InnoDB Cluster vs Tungsten Clustering
- About Continuent & Its Solutions
PRESENTER
Matthew Lang - Customer Success Director – Americas, Continuent - has over 25 years of experience in database administration, database programming, and system architecture, including the creation of a database replication product that is still in use today. He has designed highly available, scaleable systems that have allowed startups to quickly become enterprise organizations, utilizing a variety of technologies including open source projects, virtualization and cloud.
[db tech showcase Tokyo 2014] B15: Scalability with MariaDB and MaxScale by ...Insight Technology, Inc.
Scalability with MariaDB and MaxScale talks about MariaDB 10, and MaxScale, a pluggable router for your queries. These are technologies developed at MariaDB Corporation, made opensource, and will help scale your MariaDB and MySQL workloads
* Use cases of MySQL as well as edge cases of MySQL topologies using real-life examples and "war" stories
* How scalability and proxy wars make MySQL topologies more robust to serve webscale shops
* Open-source tools, utilities, and surrounding MySQL Ecosystem.
MySQL is a unique adult (now 21 years old) in many ways. It supports plugins. It supports storage engines. It is also owned by Oracle, thus birthing two branches of the popular opensource database: Percona Server and MariaDB Server. It also once spawned a fork: Drizzle. Lately a consortium of web scale users (think a chunk of the top 10 sites out there) have spawned WebScaleSQL.
You're a busy DBA having to maintain a mix of this. Or you're a CIO planning to choose one branch. How do you go about picking? Supporting multiple databases? Find out more in this talk. Also covered is a deep-dive into what feature differences exist between MySQL/Percona Server/MariaDB/WebScaleSQL, how distributions package the various databases differently. Within the hour, you'll be informed about the past, the present, and hopefully be knowledgeable enough to know what to pick in the future.
Note, there will also be coverage of the various trees around WebScaleSQL, like the Facebook tree, the Alibaba tree as well as the Twitter tree.
Webinar Slides: MySQL HA/DR/Geo-Scale - High Noon #7: ClusterControlContinuent
Severalnines’ ClusterControl vs. Continuent Tungsten Clusters for MySQL
Building a Geo-Distributed, Multi-Region and Highly Available MySQL Cloud Back-End
This is the seventh of our High Noon series covering MySQL clustering solutions for high availability (HA), disaster recovery (DR), and geographic distribution.
ClusterControl uses Galera to handle the MySQL clustering, which means it uses synchronous replication. Learn in this webinar!
You may use Tungsten Clustering with native MySQL, MariaDB or Percona Server for MySQL in GCP, AWS, Azure, and/or on-premises data centers for better technological capabilities, control, and flexibility. But learn about the pros and cons!
AGENDA
- Goals for the High Noon Webinar Series
- High Noon Series: Tungsten Clustering vs Others
- Oracle InnoDB Cluster
- Key Characteristics
- Certification-based Replication
- InnoDB Cluster Multi-Site Requirements
- Limitations Using InnoDB Cluster
- How to do better MySQL HA / DR / Geo-Distribution?
- InnoDB Cluster vs Tungsten Clustering
- About Continuent & Its Solutions
PRESENTER
Matthew Lang - Customer Success Director – Americas, Continuent - has over 25 years of experience in database administration, database programming, and system architecture, including the creation of a database replication product that is still in use today. He has designed highly available, scaleable systems that have allowed startups to quickly become enterprise organizations, utilizing a variety of technologies including open source projects, virtualization and cloud.
Differences between MariaDB 10.3 & MySQL 8.0Colin Charles
MySQL and MariaDB are becoming more divergent. Learn what is different from a high level. It is also a good idea to ensure that you use the correct database for the correct job.
MariaDB Server 10.3 is a culmination of features from MariaDB Server 10.2+10.1+10.0+5.5+5.3+5.2+5.1 as well as a base branch from MySQL 5.5 and backports from MySQL 5.6/5.7. It has many new features, like a GA-ready sharding engine (SPIDER), MyRocks, as well as some Oracle compatibility, system versioned tables and a whole lot more.
MySQL features missing in MariaDB ServerColin Charles
MySQL features missing in MariaDB Server. Here's an overview from the New York developer's Unconference in February 2018. This is primarily aimed at the developers, to decide what goes into MariaDB 10.4, as opposed to users.
High level comparisons are made between MySQL 5.6/5.7 with of course MySQL 8.0 as well. Here's to ensuring MariaDB Server 10/310.4 has more "Drop-in" compatibility.
The MySQL ecosystem - understanding it, not running away from it! Colin Charles
You're a busy DBA thinking about having to maintain a mix of this. Or you're a CIO planning to choose one branch over another. How do you go about picking? Supporting multiple databases? Find out more in this talk. Also covered is a deep-dive into what feature differences exist between MySQL/Percona Server/MariaDB Server. Within 20 minutes, you'll leave informed and knowledgable on what to pick.
A base blog post to get started: https://www.percona.com/blog/2017/11/02/mysql-vs-mariadb-reality-check/
Percona ServerをMySQL 5.6と5.7用に作るエンジニアリング(そしてMongoDBのヒント)Colin Charles
Engineering that goes into making Percona Server for MySQL 5.6 & 5.7 different (and a hint of MongoDB) for dbtechshowcase 2017 - the slides also have some Japanese in it. This should help a Japanese audience to read it. If there are questions due to poor translation, do not hesitate to drop me an email (byte@bytebot.net) or tweet: @bytebot
Databases require capacity planning (and to those coming from traditional RDBMS solutions, this can be thought of as a sizing guide). Capacity planning prevents resource exhaustion. Capacity planning can be hard. This talk has a heavier leaning on MySQL, but the concepts and addendum will help with any other data store.
Lessons from {distributed,remote,virtual} communities and companiesColin Charles
A last minute talk for the people at DevOps Amsterdam, happening around the same time as O'Reilly Velocity Amsterdam 2016. Here are lessons one can learn from distributed/remote/virtual communities and companies from someone that has spent a long time being remote and distributed.
Tuning Linux for your database FLOSSUK 2016Colin Charles
Some best practices about tuning Linux for your database workloads. The focus is not just on MySQL or MariaDB Server but also on understanding the OS from hardware/cloud, I/O, filesystems, memory, CPU, network, and resources.
Having spent more than the last decade being the main point of contact for distributions shipping MySQL, then MariaDB Server, it's clear that working with distributions have many challenges. Licensing changes (when MySQL moved the client libraries from LGPL to GPL with a FOSS Exception), ABI changes, speed (or lack thereof) of distribution releases/freezes, supporting the software throughout the lifespan of the distribution, specific bugs due to platforms, and a lot more will be discussed in this talk. Let's not forget the politics. How do we decide "tiers" of importance for distributions? As a bonus, there will be a focus on how much effort it took to "replace" MySQL with MariaDB.
Benefits: if you're making a distribution, this is the point of view of the upstream package makers. Why are distribution statistics important to us? Do we monitor your bugs system or do you have a better escalation to us? How do we test to make sure things are going well before release. This and more will be spoken about.
As an upstream project (package), we love nothing more than being available everywhere. But time and energy goes into making this is so as there are quirks in every distribution.
Meet MariaDB Server 10.1 London MySQL meetup December 2015Colin Charles
Meet MariaDB Server 10.1, the server that got released recently. Presented at the London MySQL Meetup in December 2015. Learn about the new features in MariaDB Server, especially around the focus of what we did to improve security.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
MySQL in the Cloud
1. MySQL in the Cloud
Colin Charles, MariaDB/SkySQL Ab
colin@mariadb.org | byte@bytebot.net
http://mariadb.com/ | http://mariadb.org/
http://bytebot.net/blog/ | @bytebot on Twitter
LinuxCon/CloudOpen, New Orleans, Louisiana, USA
17 September 2013
1
2. whoami
• Chief Evangelist, MariaDB at Monty Program
SkySQL
• Formerly MySQL AB/Sun Microsystems
• Using/developing/hacking on MySQL since
2000
• Previously on FESCO for The Fedora
Project, and worked on OpenOffice.org
(2000-2005)
2
3. Agenda
• MySQL as a service offering (DBaaS)
• Choices
• Considerations
• MySQL versions & access
• Costs
• Deeper into RDS
• Should you run this on EC2 or an equivalent?
• Conclusion
3
4. MySQL as a service
• Database as a Service (DBaaS)
• MySQL available on-demand, without any
installation/configuration of hardware/
software
• Pay-per-usage based
• Provider maintains MySQL, you don’t
maintain, upgrade, or administer the database
4
5. New way of
deployment
• Enter a credit card
number
• call API (or use the GUI)
ec2-run-instances ami-
xxx -k ${EC2_KEYPAIR} -t
m1.large
nova boot --image
centos6-x86_64 --flavor
m1.large db1
5
credit: http://www.flickr.com/photos/68751915@N05/6280507539/
6. Why DBaaS?
• “Couldn’t we just have a few more servers
to handle the traffic spike during the
elections?”
• Don’t have a lot of DBAs, optimise for
operational ease
• Rapid deployment & scale-out
6
7. Your choices today
• Amazon Web Services Relational Database
Service (RDS)
• Rackspace Cloud Databases
• Google Cloud SQL
• HP Cloud Relational Database
7
8. There are more
• Jelastic - PaaS offering MySQL, MariaDB
• ClearDB - MySQL partnered with heroku,
appfog,Azure clouds
• Joyent - Image offers Percona MySQL
• Xeround - 2 weeks notice...
8
9. Whom we won’t be
covering
• GenieDB - globally distributed MySQL as a
service, master-master replication, works
on EC2, Rackspace, Google Compute
Engine, HP Cloud
• ScaleDB - promises write scaling, HA
clustering, etc. replacing InnoDB/MyISAM
9
10. Regions & Availability
Zones
• Region: a data centre
location, containing
multiple Availability
Zones
• Availability Zone (AZ):
isolated from failures
from other AZs + low-
latency network
connectivity to other
zones in same region
10
11. Location, location,
location
• AWS RDS: US East (N.Virginia), US West
(Oregon), US West (California), EU (Ireland),
APAC (Singapore),APAC (Tokyo),APAC
(Sydney), South America (São Paulo), GovCloud
• Rackspace: USA (Dallas DFW, Chicago ORD,
N.Virginia IAD),APAC (Sydney), EU (London)*
• Google Cloud SQL: US, EU
• HP Cloud: US-East (Virginia), US-West
11
12. Service Level
Agreements (SLA)
• AWS - 99.95% in a calendar month
• Rackspace - 99.9% in a calendar month
• Google - 99.95% in a calendar month
• HP Cloud - no SLA yet, services in beta
• SLAs exclude “scheduled maintenance”
• AWS is 30 minutes/week, so really 99.65%
12
13. Support
• AWS - forums; $49/mo gets email; $100+
phone #
• Rackspace - live chat, phone #, forums
• Google - forums; $150/mo gets support
portal; $400+ for phone #
• HP Cloud - phone #, chat, customer forum
13
14. Who manages this?
• AWS: self-management, Enterprise ($15k+)
• Rackspace: $100 + 0.04 cents/hr over
regular pricing
• Google: self-management
• HP Cloud: self-management
14
15. MySQL versions
• AWS: MySQL Community 5.1.71, 5.5.33,
5.6.13
• Rackspace: MySQL Community 5.1
• Google: MySQL Community 5.5
• HP Cloud: Percona Server 5.5.28
15
16. Access methods
• AWS - within Amazon, externally via mysql
client,API access.
• Rackspace - private hostname within Rackspace
network, standard mysql client,API access.
• Google - within AppEngine, or a command line
Java tool (gcutil)
• HP Cloud - within HP Cloud, externally via
client (trove-cli, reddwarf) or API access.
16
17. Can you configure
MySQL?
• You don’t access my.cnf
naturally
• In AWS you have
parameter groups which
allow configuration of
MySQL
17
source: http://www.mysqlperformanceblog.com/2013/08/21/amazon-rds-with-mysql-5-6-configuration-variables/
18. Cost
• Subscribe to relevant newsletters of your
services
• Cost changes rapidly, plus you get new instance
types and new features (IOPS)
• Don’t forget network access costs
• Monitor your costs daily, hourly if possible
(EC2 instances can have spot pricing)
• https://github.com/ronaldbradford/aws
18
20. Costs:AWS II
• Medium instances (3.75GB) useful for testing
($2,411/yr)
• Large instance (7.5GB) production ready ($4,777/
yr)
• XL instance (15GB, 8ECUs) ($9,555/yr)
• m2.2XL instance (34GB, 13ECUs, 500Mbps PIOPS)
($16,568/yr)
• m2.4XL instance (68GB, 26ECUs, 1000Mbps PIOPS)
($33,048/yr)
20
21. Costs: Rackspace
• Option to have regular Cloud Database or
Managed Instances
• 4GB instance (testing) is $3,504/yr
• 8GB instance (production) is $6,658/yr
• Consider looking at I/O priority, and the
actual TPS you get
21
22. Costs: Google
• You must enable billing before you create Cloud
SQL instances
• https://developers.google.com/cloud-sql/docs/billing
• Testing (D8 - 4GB RAM) - ($4,274.15)
• XL equivalent for production (D16 - 8GB RAM) -
($8,548.30)
• Packages billing plans are cheaper than per-use
billing plans
22
24. Where do you host
your application?
• Typically within the compute clusters of the
service you’re running the DBaaS in
• This also means your language choices are
limited based on what the platform offers
(eg.AppEngine only recently started
offering PHP)
24
25. RDS: Multi-AZ
• Provides enhanced durability (synchronous
data replication)
• Increased availability (automatic failover)
• Warning: can be slow (1-10 mins+)
• Easy GUI administration
• Doesn’t give you another usable “read-
replica” though
25
26. External replication
• MySQL 5.6 you can do RDS -> Non-RDS
• enable backup retention, you now have
binlog access
• You still can’t replicate INTO RDS
• use Tungsten Replicator
• also supports going from RDS to
Rackspace/etc.
26
27. MySQL 5.6, MariaDB
10
• MySQL 5.6 in RDS provides crash-safe slaves, the
InnoDB memcached interface, online schema
changes, full-text InnoDB indexes, optimizer
improvements, INFORMATION_SCHEMA
enhancements, scalability/replication
improvements, PERFORMANCE_SCHEMA
enhancements
• MariaDB 10 has that, plus multi-source
replication, GTIDs that don’t require full restarts,
threadpool, audit plugin and more
27
28. Getting started
• Importing data into the cloud?
• RDS: mysqldump is a good choice
• Google Cloud SQL is only via existing
Google Cloud Storage
• Upgrading from RDS 5.5 to RDS 5.6?
• mysqldump!
28
29. Handling backups
• You don’t get to use xtrabackup!
• Google Cloud SQL automates backups (has
a backup window)
• Amazon has automated backups (with
point-in-time recovery), with full daily
snapshots (has a backup window).
29
30. Monitoring
• Options are limited,AWS has the best
options currently available
• Today you have CloudWatch
• Google has basic read/write graphs
30
31. Storage Engines
• MySQL (/MariaDB) has many
• cool ones include TokuDB, SPIDER,
CONNECT, CassandraSE
• You basically use InnoDB and MyISAM with
cloud solutions
• MyISAM on RDS won’t guarantee point-
in-time recovery, snapshot restore
31
32. High Availability
• Plan for node failures
• Don’t assume node provisioning is quick
• Backup, backup, backup!
• “Bad” nodes exist
• HA is not equal across options - RDS wins
so far
32
33. Unsupported features
• AWS: GTIDs, InnoDB Cache Warming,
InnoDB transportable tablespaces,
authentication plugins, semi-sync replication
• Google: UDFs, replication, LOAD DATA
INFILE, INSTALL PLUGIN, SELECT ... INTO
OUTFILE
33
34. Provisioned IOPS
• Only available on Amazon
• Faster, predictable, consistent I/O
performance with low latencies
• Good throughput, RAID on backed
• EBS is more reliable
34
35. More on RDS
• log access via API
• no SUPER access to skip replication errors
easily
• sync_binlog=0 not available
• no OS access (sar, ps, swap?, tcpdump)
• https://github.com/boto/boto
35
36. Warning: automatic
upgrades
• Regressions happen even with a minor
version upgrade in the MySQL world
• InnoDB update that modifies rows PK
triggers recursive behaviour until all disk
space is exceeded? 5.5.24->5.5.25 (fixed:
5.5.25a)
• Using query cache for partitioned tables?
Disabled since 5.5.22->5.5.23!
36
37. Benchmarking for use
• sysbench
• OLTP test, use tables with 20M rows and 20M
transactions, check 1-128 threads/run (run this
on RDS, Rackspace)
• June 2013, tps, performance per dollar, Rackspace
delivers more performance across all flavours
except 512MB instance
• Yahoo! Cloud Serving Benchmark
• https://github.com/brianfrankcooper/YCSB
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38. Roadmaps?
• There don’t seem to be public roadmaps.
You find out when there’s a change!
• Expect more to move to MySQL 5.6
• except Google, who will probably move
to MariaDB 10.0
• maybe Rackspace is up in the air?
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39. Running MySQL in EC2
• Can do multiple geographic
regions via replication
• Run just one Percona Server/
MariaDB server/instance
• Use additional EBS volumes for
InnoDB tablespaces
• RAID EBS volumes (RAID1)
• Warm up data partitions, mount
partitions with noatime,
nodirtime
• Vertical scaling with SSD-backed
storage
• Monitoring with nagios
• Snapshot backups and save to S3
• Can use Elastic Load Balancer
• Can use spot instances
• Can use tools like MHA to
provide automatic failover
• Can use MariaDB Galera Cluster/
Percona XtraDB Cluster
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40. Some closing thoughts
• Hardware varies per region
• Sometimes, software manageability varies
per region
• Beware cost on your credit card!
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